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		<div id="HeadBox"><a href="index.html">English Version</a></div>
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				<h1>Andrew Cao 曹路</h1>
				<p>
					I am a 2th year MSE student at <a href="http://english.pku.edu.cn/">Peking University</a> working with <a href="http://www.ss.pku.edu.cn/index.php/teacherteam/teacherlist/1640-%E4%BF%9E%E6%95%AC%E6%9D%BE">Jingsong Yu</a>.
					I have also worked with <a href='http://cvgl.stanford.edu/silvio/'><a href="https://itu.edu/faculty/may-huang">Dr. May Huang</a>,
					<a href="https://www.linkedin.com/in/eric-chen-a645402b/">Eric Chen</a> and <a href="https://itu.edu/spotlight/Karl-Wang">Dr. Karl L. Wang</a>
					under double-degree joint project at <a href="https://itu.edu/">International Technological University</a>.
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				<p>
					Before coming to Peking University, I have worked with <a href='http://www.hainu.edu.cn/stm/xinxi/2015115/10409855.shtml'>Zhuhua Hu</a> and Yaochi Zhao during my undergrad at Hainan University.
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					Over the summers, I've been lucky to be an intern with Kaifu Wang and Shouye Peng at TAL Education Group Intelligent R&D Department.
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				<p><i><b>兴趣领域:</b> My recent research interests focus on 自然语言处理, 深度学习, 数据挖掘, 机器人控制系统，计算机视觉.</i></p>

				<i style="color: red;">I am currently looking for partners to do more projects. Please feel free to contact with me :)</i>

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				<b>动态</b> &nbsp;&nbsp; <a href="https://github.com/andrewcao95/personal-profile-list/blob/master/news/news.md">more detail</a>
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				<li>(2018/12/01) I won the honorary title of merit student of Peking University.</li>

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				<b>联系方式</b>
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					<p>Email: <a href="mailto:andrewcao95@gmail.com">andrewcao95@gmail.com</a></p>
					<p>Github: <a href="https://github.com/andrewcao95">https://github.com/andrewcao95</a></p>
					<p>Linkedin: <a href="https://www.linkedin.com/in/andrewcao95">https://www.linkedin.com/in/andrewcao95</a></p>
					<p>Kaggle: <a href="https://www.kaggle.com/andrewcao95">https://www.kaggle.com/andrewcao95</a></p>
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				<i>
					<p>Resume: <a href="files/CAOLU_CV_EN.pdf">[in English]</a>  &nbsp;&nbsp;&nbsp; <a href="files/CAOLU_CV_EN.pdf">[in Chinese]</a>  &nbsp;&nbsp;&nbsp; (10/22/2018)</p>
					<p>Leetcode: <a href="https://leetcode.com/andrewcao95">https://leetcode.com/andrewcao95</a></p>
					<p>Photograph Gallery: <a href="https://andrewcao95.tuchong.com">https://andrewcao95.tuchong.com</a></p>
					<!-- <p>Mail Address: Peking University, No.5 Yiheyuan Rd, Haidian District, Beijing, China(100871)</p> -->
					<p>Mail Address: 2711 N 1st St, San Jose, California, United States 95134</p>
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				<b>教育背景</b>
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				<p>Dec. 2018 - Now, 硕士, 计算机工程, <a href="https://itu.edu/">International Technological University</a> (美国加州 旧金山湾区)</p>
				<p>Sep. 2017 - Now, 硕士, 软件工程, <a href="http://english.pku.edu.cn/">北京大学</a> (中国 北京)</p>
				<p>Sep. 2013 - Jul. 2017, 学士,	网络工程, <a href="http://www.hainu.edu.cn/">海南大学</a> (海南 海口)</p>
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				<b>工作经历</b>
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				<p>Jan. 2019 - Now, Artificial Intelligence Research Lab, International Technological University (San Francisco Bay Area, California, United States), Research Assistant</p>
				<p>Jul. 2018 - Dec. 2018, Intelligent R&D Department, TAL Education Group[top1 education & technology enterprise in China] (Beijing City, China), Intern (Nature Language Processing)</p>
				<p>Jan. 2018 - Feb. 2018, Science & Technology Big Data Research Center, Tsinghua University (Beijing City, China), Intern (Data Mining)</p>
				<p>Dec. 2016 - Apr. 2017, 网络工程系和水产养殖系, 海南大学 (中国 海口), 研究助理</p>
				<p>Feb. 2016 - Jul. 2016, 南海海洋资源利用国家重点实验室 (中国 海口), 研究助理</p>
				<p>Sep. 2015 - Jan. 2016, Network System Operation Department, Network Technology Center of Hainan University (Haikou City, China), Operations Assistant</p>
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				<b>部分项目</b> &nbsp;&nbsp; <a href="https://github.com/andrewcao95/personal-profile-list/blob/master/projects/projects.md">see more</a>
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					<p><b>Artificial intelligence poetry robot</b></p>
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						<i><p>co-worker: Lu Cao, <a href="https://github.com/xzwj">Yuan Tian, <a href="http://iir.ruc.edu.cn/~chenj/index.html">Jun Chen</a></p></i>
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							<a src= "">[detail and code]</a>
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				<b>部分论文</b> &nbsp;&nbsp; <a href="https://github.com/andrewcao95/personal-profile-list/blob/master/papers/papers.md">see more</a>
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					<p><b>认知无线网络中一种对抗SSDH攻击的序贯压缩频谱感知算法</b></p>
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						<p><i>co-author: Zhuhua Hu, Yong Bai, Lu Cao, Mengxing Huang, Mingshan Xie (2018/11/11 - 2018/12/11)</i></p>
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							Spectrum sensing is one of the key technologies in wireless wideband communication.
							There are still challenges in respect of how to realize fast and robust wideband spectrum sensing technology.
							In this paper, a novel nonreconstructed sequential compressed wideband spectrum sensing algorithm (NSCWSS) is proposed.
							Firstly, the algorithm uses a sequential spectrum sensing method based on history memory and reputation to ensure the robustness of the algorithm.
							Secondly, the algorithm uses the strategy of compressed sensing without reconstruction, which thus ensures the sensing agility of the algorithm.
							The algorithm is simulated and analyzed by using the centralized cooperative sensing.
							The theoretical analysis and simulation results reveal that, under the condition of ensuring the certain detection probability,
							the proposed algorithm effectively reduces complex computation of signal reconstruction, significantly reducing the wideband spectrum sampling rate.
							At the same time, in the cognitive wideband communication scenarios, the algorithm also achieves a better defense against the SSDF attack in spectrum sensing.
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							<a href= "https://doi.org/10.1155/2018/4782718">[paper]</a>
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					<p><b>权重约束AdaBoost鱼眼识别及改进Hough圆变换瞳孔智能测量</b></p>
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						<p><i>co-author: Zhuhua Hu, Yiran Zhang, Yaochi Zhao, Lu Cao, Yong Bai, Mengxing Huang</i></p>
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							针对传统鱼眼瞳孔直径测量方法耗时、耗力，且数据主观性强的问题，该文提出基于权重约束AdaBoost和改进Hough圆变换的鱼眼瞳孔直径智能测量方法。
							首先，利用工业相机采集实验板上的鱼图像，从正负鱼眼图像样本中训练出基于权重约束AdaBoost算法的鱼眼分类器；
							然后，采用该分类器对试验图像进行检测，将检测到的鱼眼局部图从整体图中分离出来；
							最后，采用改进的Hough圆变换检测出鱼眼的瞳孔，并计算得到瞳孔直径。对100条金鲳鱼进行试验，
							鱼眼分类精度达97.1%，瞳孔正确检测率达94.2%，相比改进前分别提升了1.7个百分点和10.5个百分点，与人工测量瞳孔直径值的平均偏差为6.5%，
							比改进前低了5.9个百分点，总的平均测量时间为324.371 ms，比改进前减少了10.707 ms。
							试验证明：该文提出的方法能够精确、实时、自动地测量出鱼眼瞳孔的直径，
							有效避免了传统测量方式的复杂性和测量数据的主观性，可为鱼体生长状况评估、良种选育提供重要参考。
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							<a href= "https://www.ingentaconnect.com/content/tcsae/tcsae/2017/00000033/00000023/art00029">[paper]</a>
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						<p><i>co-author: Zhuhua Hu, Lu Cao, Yiran Zhang, Yaochi Zhao (2017/02)</i></p>
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							<a href= "http://www.en.cnki.com.cn/Article_en/CJFDTotal-HDXY201702009.htm">[paper]</a>
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				<b>Selected Patent</b> &nbsp;&nbsp; <a href="https://github.com/andrewcao95/personal-profile-list/blob/master/patents/patents.md">see more</a>
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					<p><b>一种鱼眼特征自动测量方法</b></p>
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						<p><i>co-author: Zhuhua Hu, Yaochi Zhao, Lu Cao (2017-07-17)</i></p>
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							本发明涉及一种鱼眼特征自动测量方法，所述方法包括：采集鱼例图像并去除背景；
							提取去除背景的鱼例图像中的鱼眼图像；根据鱼眼图像确定鱼眼像素尺寸，并将所述鱼眼像素尺寸转换为实际尺寸；
							采集鱼例图像需要构建采集鱼例图像装置；所述采集鱼例图像装置包括：标准平台、机械手臂和采集相机；
							所述采集相机与标准平台通过机械手臂连接；标准平台用于盛放待测鱼体；
							机械手臂用于调节采集相机与标准平台的距离和位置；采集相机用于拍摄鱼例图像。
							本发明提供的方法，利用计算机视觉技术和图像处理技术实现无接触式自动测量，
							大大提高测量效率的同时保证了测量数据的精确性和稳定性。
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							<a href= "https://patents.google.com/patent/CN107462221A/en">[link]</a>
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		<div id="BottomBox">Last Updated on 12/01/2018.</div>

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